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IoT-Based Strawberry Disease Prediction System for Smart Farming

Crop diseases cannot be accurately predicted by merely analyzing individual disease causes. Only through construction of a comprehensive analysis system can users be provided with predictions of highly probable diseases. In this study, cloud-based technology capable of handling the collection, analy...

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Detalles Bibliográficos
Autores principales: Kim, Sehan, Lee, Meonghun, Shin, Changsun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263482/
https://www.ncbi.nlm.nih.gov/pubmed/30463363
http://dx.doi.org/10.3390/s18114051
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author Kim, Sehan
Lee, Meonghun
Shin, Changsun
author_facet Kim, Sehan
Lee, Meonghun
Shin, Changsun
author_sort Kim, Sehan
collection PubMed
description Crop diseases cannot be accurately predicted by merely analyzing individual disease causes. Only through construction of a comprehensive analysis system can users be provided with predictions of highly probable diseases. In this study, cloud-based technology capable of handling the collection, analysis, and prediction of agricultural environment information in one common platform was developed. The proposed Farm as a Service (FaaS) integrated system supports high-level application services by operating and monitoring farms as well as managing associated devices, data, and models. This system registers, connects, and manages Internet of Things (IoT) devices and analyzes environmental and growth information. In addition, the IoT-Hub network model was constructed in this study. This model supports efficient data transfer for each IoT device as well as communication for non-standard products, and exhibits high communication reliability even in poor communication environments. Thus, IoT-Hub ensures the stability of technology specialized for agricultural environments. The integrated agriculture-specialized FaaS system implements specific systems at different levels. The proposed system was verified through design and analysis of a strawberry infection prediction system, which was compared with other infection models.
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spelling pubmed-62634822018-12-12 IoT-Based Strawberry Disease Prediction System for Smart Farming Kim, Sehan Lee, Meonghun Shin, Changsun Sensors (Basel) Article Crop diseases cannot be accurately predicted by merely analyzing individual disease causes. Only through construction of a comprehensive analysis system can users be provided with predictions of highly probable diseases. In this study, cloud-based technology capable of handling the collection, analysis, and prediction of agricultural environment information in one common platform was developed. The proposed Farm as a Service (FaaS) integrated system supports high-level application services by operating and monitoring farms as well as managing associated devices, data, and models. This system registers, connects, and manages Internet of Things (IoT) devices and analyzes environmental and growth information. In addition, the IoT-Hub network model was constructed in this study. This model supports efficient data transfer for each IoT device as well as communication for non-standard products, and exhibits high communication reliability even in poor communication environments. Thus, IoT-Hub ensures the stability of technology specialized for agricultural environments. The integrated agriculture-specialized FaaS system implements specific systems at different levels. The proposed system was verified through design and analysis of a strawberry infection prediction system, which was compared with other infection models. MDPI 2018-11-20 /pmc/articles/PMC6263482/ /pubmed/30463363 http://dx.doi.org/10.3390/s18114051 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kim, Sehan
Lee, Meonghun
Shin, Changsun
IoT-Based Strawberry Disease Prediction System for Smart Farming
title IoT-Based Strawberry Disease Prediction System for Smart Farming
title_full IoT-Based Strawberry Disease Prediction System for Smart Farming
title_fullStr IoT-Based Strawberry Disease Prediction System for Smart Farming
title_full_unstemmed IoT-Based Strawberry Disease Prediction System for Smart Farming
title_short IoT-Based Strawberry Disease Prediction System for Smart Farming
title_sort iot-based strawberry disease prediction system for smart farming
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263482/
https://www.ncbi.nlm.nih.gov/pubmed/30463363
http://dx.doi.org/10.3390/s18114051
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